Subscribe to the gold package and get unlimited access to Shamra Academy
Register a new userThermal conductivity of micro/nano-porous polymers: Prediction models and applications
118
0
0.0
(
0
)
Ask ChatGPT about the research
No Arabic abstract
Micro/nano porous polymeric material is considered a unique industrial material due to its extremely low thermal conductivity, low density, and high surface area. Therefore, it is necessary to establish an accurate thermal conductivity prediction model suiting their applicable conditions and provide a theoretical basis for expanding of their applications. In this work, the development of the calculation model of equivalent thermal conductivity of micro/nano porous polymeric materials in recent years was summarized. Firstly, it reviews the process of establishing the overall equivalent thermal conductivity calculation model for micro/nano porous polymers. Then, the predicted calculation models of thermal conductivity are introduced according to the conductive thermal conductivity models and the radiative thermal conductivity models separately. In addition, the thermal conduction part is divided into the gaseous thermal conductivity model, solid thermal conductivity model and gas-solid coupling model. Finally, it is concluded that, compared with other porous materials, there are few studies on heat transfer of micro/nano porous polymers, especially on the special heat transfer mechanisms such as scale effects at the micro/nanoscale. In particular, the following aspects of porous polymers still need to be further studied: micro scaled thermal radiation, heat transfer characteristics of special morphologies at the nanoscale, heat transfer mechanism and impact factors of micro/nano porous polymers. Such studies would provide a more accurate prediction of thermal conductivity and a wider application in energy conversion and storage systems.
rate research
Read More
We report measurements and Monte Carlo simulations of thermal conductivity of porous 100nm- thick silicon membranes, in which size, shape and position of the pores were varied randomly. Measurements using 2-laser Raman thermometry on both plain membrane and porous membranes revealed more than 10-fold reduction of thermal conductivity compared to bulk silicon and six-fold reduction compared to non-patterned membrane for the sample with 37% filling fraction. Using Monte Carlo solution of the Boltzmann transport equation for phonons we compared different possibilities of pore organization and its influence on the thermal conductivity of the samples. The simulations confirmed that the strongest reduction of thermal conductivity is achieved for a distribution of pores with arbitrary shapes that partly overlap. Up to 15% reduction of thermal conductivity with respect to the purely circular pores was predicted for a porous membrane with 37% filling fraction. The effect of pore shape, distribution and surface roughness is further discussed.
Polymers are usually considered as thermal insulators and their applications are limited by their low thermal conductivity. However, recent studies showed that certain polymers have surprisingly high thermal conductivity, some of which are comparable to that in poor metals or even silicon. In this review, we outline the experimental achievements and theoretical progress of thermal transport in polymers and their nanocomposites. The open questions and challenges of existing theories are discussed. Special attention is given to the mechanism of thermal transport, the enhancement of thermal conductivity in polymer nanocomposites/fibers, and their potential application as thermal interface materials.
Nanograined bulk alloys based on bismuth telluride (Bi2Te3) are the dominant materials for room-temperature thermoelectric applications. In numerous studies, existing bulk phonon mean free path (MFP) spectra predicted by atomistic simulations suggest sub-100 nm grain sizes are necessary to reduce the lattice thermal conductivity by decreasing phonon MFPs. This is in contrast with available experimental data, where a remarkable thermal conductivity reduction is observed even for micro-grained Bi2Te3 samples. In this work, first-principles phonon MFPs along both the in-plane and cross-plane directions are re-computed for bulk Bi2Te3. These phonon MFPs can explain new and existing experimental data on flake-like Bi2Te3 nanostructures with various thicknesses. For polycrystalline Bi2Te3-based materials, a better explanation of the experimental data requires further consideration of the grain-boundary thermal resistance that can largely suppress the transport of high-frequency optical phonons.
Porous materials provide a large surface to volume ratio, thereby providing a knob to alter fundamental properties in unprecedented ways. In thermal transport, porous nanomaterials can reduce thermal conductivity by not only enhancing phonon scattering from the boundaries of the pores and therefore decreasing the phonon mean free path, but also by reducing the phonon group velocity. Here we establish a structure-property relationship by measuring the porosity and thermal conductivity of individual electrolessly etched single crystalline silicon nanowires using a novel electron beam heating technique. Such porous silicon nanowires exhibit extremely low diffusive thermal conductivity (as low as 0.33 Wm-1K-1 at 300K for 43% porosity), even lower than that of amorphous silicon. The origin of such ultralow thermal conductivity is understood as a reduction in the phonon group velocity, experimentally verified by measuring the Young modulus, as well as the smallest structural size ever reported in crystalline Silicon (less than 5nm). Molecular dynamics simulations support the observation of a drastic reduction in thermal conductivity of silicon nanowires as a function of porosity. Such porous materials provide an intriguing platform to tune phonon transport, which can be useful in the design of functional materials towards electronics and nano-electromechanical systems.
Two theory-driven models of electron ionization cross sections, the Binary-Encounter-Bethe model and the Deutsch-Mark model, have been design and implemented; they are intended to extend the simulation capabilities of the Geant4 toolkit. The resulting values, along with the cross sections included in the EEDL data library, have been compared to an extensive set of experimental data, covering more than 50 elements over the whole periodic table.
Log in to be able to interact and post comments
comments
Fetching comments
Sign in to be able to follow your search criteria
